MétaCan
Menu
Back to cohort
Record W4409148943 · doi:10.1093/braincomms/fcaf126

Sleep abnormalities are associated with greater cognitive deficits and disease activity in Huntington's disease: a 12-year polysomnographic study

2025· article· en· W4409148943 on OpenAlexaboutno aff
Zanna J. Voysey, Anna Goodman, Lorraine Rogers, Jonathan A Holbrook, Alpár S. Lázár, Roger A. Barker

Bibliographic record

VenueBrain Communications · 2025
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsnot available
FundersCambridge Centre for Parkinson-PlusMedical Research CouncilNational Institute for Health and Care ResearchCure Parkinson's TrustUK Research and InnovationNIHR Cambridge Biomedical Research CentreWellcome TrustGuarantors of BrainDepartment of Health and Social CareCure Parkinson’s TrustCure Huntington's Disease InitiativeCHDI Foundation
KeywordsHuntington's diseaseDiseaseSleep (system call)MedicinePolysomnographyCognitionAudiologyPsychologyNeurosciencePsychiatryInternal medicineElectroencephalography

Abstract

fetched live from OpenAlex

Abstract Increasing evidence suggests that the sleep pathology associated with neurodegenerative diseases can in turn exacerbate both the cognitive deficits and underlying pathobiology of these conditions. Treating sleep may therefore bear significant, even disease-modifying, potential for these conditions, but how best and when to do so remains undetermined. Huntington's disease, by virtue of being an autosomal dominant neurodegenerative disease presenting in mid-life, presents a key ‘model’ condition through which to advance this field. To date, however, there has been no clinical longitudinal study of sleep abnormalities in Huntington's disease and no robust interrogation of their association with disease onset, cognitive deficits and markers of disease activity. Here, we present the first such study. Huntington's disease gene carriers (n = 28) and age- and sex-matched controls (n = 21) were studied at baseline and 10- and 12-year follow-up. All Huntington's disease gene carriers were premanifest at baseline and were stratified at follow-up into ‘prodromal/manifest’ versus ‘premanifest’ groups. Objective sleep abnormalities were assessed through two-night inpatient polysomnography and 2-week domiciliary actigraphy, and their association was explored against Montreal Cognitive Assessment, Trail A/B task, Symbol Digit Modalities Task (SDMT), Hopkins Verbal Learning Task (HVLT) and Montgomery–Asberg Depression Rating Scale (MADRS) scores, plus serum neurofilament light levels. Statistical analysis incorporated cross-sectional ANOVA, longitudinal repeated measures linear models and regressions adjusted for multiple confounders including disease stage. Fifteen Huntington's disease gene carriers phenoconverted to prodromal/early manifest Huntington's disease by study completion. At follow-up, these gene carriers showed more frequent sleep stage changes (P ≤ 0.001, ηp2 = 0.62) and higher levels of sleep maintenance insomnia (defined by wake after sleep onset, P = 0.002, ηp2 = 0.52). The latter finding was corroborated by nocturnal motor activity patterns on follow-up actigraphy (P = 0.004, ηp2 = 0.32). Greater sleep maintenance insomnia was associated with greater cognitive deficits (Trail A P ≤ 0.001, R2 = 0.78; SDMT P = 0.008, R2 = 0.63; Trail B P = 0.013, R2 = 0.60) and higher levels of neurofilament light (P = 0.015, R2 = 0.39). Longitudinal modelling suggested that sleep stage instability accrues from the early premanifest phase, whereas sleep maintenance insomnia emerges closer to phenoconversion. Baseline sleep stage instability was able to discriminate those who phenoconverted within the study period from those who remained premanifest (area under curve = 0.81, P = 0.024). These results demonstrate that the key sleep abnormalities of premanifest/early Huntington's disease are sleep stage instability and sleep maintenance insomnia and suggest that the former bears value in predicting disease onset, while the latter is associated with greater disease activity and cognitive deficits. Intervention studies to interrogate causation within this association could not only benefit patients with Huntington's disease but also help provide fundamental proof-of-concept findings for the wider sleep–neurodegeneration field.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.896

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.041
GPT teacher head0.291
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueBrain CommunicationsSame topicGenetic Neurodegenerative DiseasesFrench-language works237,207